Long-term exposure to air pollution has been associated with mortality in urban cohort studies. Few studies have investigated this association in large-scale population registries, including ...non-urban populations.
The aim of the study was to evaluate the associations between long-term exposure to air pollution and nonaccidental and cause-specific mortality in the Netherlands based on existing national databases.
We used existing Dutch national databases on mortality, individual characteristics, residence history, neighborhood characteristics, and national air pollution maps based on land use regression (LUR) techniques for particulates with an aerodynamic diameter ≤ 10 μm (PM10) and nitrogen dioxide (NO2). Using these databases, we established a cohort of 7.1 million individuals ≥ 30 years of age. We followed the cohort for 7 years (2004-2011). We applied Cox proportional hazard models adjusting for potential individual and area-specific confounders.
After adjustment for individual and area-specific confounders, for each 10-μg/m3 increase, PM10 and NO2 were associated with nonaccidental mortality hazard ratio (HR) = 1.08; 95% CI: 1.07, 1.09 and HR = 1.03; 95% CI: 1.02, 1.03, respectively, respiratory mortality (HR = 1.13; 95% CI: 1.10, 1.17 and HR = 1.02; 95% CI: 1.01, 1.03, respectively), and lung cancer mortality (HR = 1.26; 95% CI: 1.21, 1.30 and HR = 1.10 95% CI: 1.09, 1.11, respectively). Furthermore, PM10 was associated with circulatory disease mortality (HR = 1.06; 95% CI: 1.04, 1.08), but NO2 was not (HR = 1.00; 95% CI: 0.99, 1.01). PM10 associations were robust to adjustment for NO2; NO2 associations remained for nonaccidental mortality and lung cancer mortality after adjustment for PM10.
Long-term exposure to PM10 and NO2 was associated with nonaccidental and cause-specific mortality in the Dutch population of ≥ 30 years of age.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
BACKGROUND: Specific characteristics of particulate matter (PM) responsible for associations with respiratory health observed in epidemiological studies are not well established. High correlations ...among, and differential measurement errors of, individual components contribute to this uncertainty. OBJECTIVES: We investigated which characteristics of PM have the most consistent associations with acute changes in respiratory function in healthy volunteers. METHODS: We used a semiexperimental design to accurately assess exposure. We increased exposure contrast and reduced correlations among PM characteristics by exposing volunteers at five different locations: an underground train station, two traffic sites, a farm, and an urban background site. Each of the 31 participants was exposed for 5 hr while exercising intermittendy, three to seven times at different locations during March— October 2009. We measured PM₁₀ , PM₂.₅, particle number concentrations (PNC), absorbance, elemental/organic carbon, trace metals, secondary inorganic components, endotoxin content, gaseous pollutants, and PM oxidative potential. Lung function FEV₁ (forced expiratory volume in 1 sec), FVC (forced vital capacity), FEF₂₅_₇₅ (forced expiratory flow at 25-75% of vital capacity), and PEF (peak expiratory flow) and fractional exhaled nitric oxide (FENQ) were measured before and at three time points after exposure. Data were analyzed with mixed linear regression. RESULTS: An interquartile increase in PNC (33,000 particles/cm³) was associated with an 11% 95% confidence interval (CI): 5, 17% and 12% (95% CI: 6, 17%) FENO increase over baseline immediately and at 2 hr postexposure, respectively. A 7% (95% CI: 0.5, 14%) increase persisted until the following morning. These associations were robust and insensitive to adjustment for other pollutants. Similarly consistent associations were seen between FVC and FEV₁ with PNC, NO₂ (nitrogen dioxide), and NOX (nitrogen oxides). CONCLUSIONS: Changes in PNC, NO₂, and NOX were associated with evidence of acute airway inflammation (i. e., FENO) and impaired lung function. PM mass concentration and PM₁₀ oxidative potential were not predictive of the observed acute responses.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Current air quality standards for particulate matter (PM) use the PM mass concentration PM with aerodynamic diameters ≤ 10 μm (PM(10)) or ≤ 2.5 μm (PM(2.5)) as a metric. It has been suggested that ...particles from combustion sources are more relevant to human health than are particles from other sources, but the impact of policies directed at reducing PM from combustion processes is usually relatively small when effects are estimated for a reduction in the total mass concentration.
We evaluated the value of black carbon particles (BCP) as an additional indicator in air quality management.
We performed a systematic review and meta-analysis of health effects of BCP compared with PM mass based on data from time-series studies and cohort studies that measured both exposures. We compared the potential health benefits of a hypothetical traffic abatement measure, using near-roadway concentration increments of BCP and PM(2.5) based on data from prior studies.
Estimated health effects of a 1-μg/m3 increase in exposure were greater for BCP than for PM(10) or PM(2.5), but estimated effects of an interquartile range increase were similar. Two-pollutant models in time-series studies suggested that the effect of BCP was more robust than the effect of PM mass. The estimated increase in life expectancy associated with a hypothetical traffic abatement measure was four to nine times higher when expressed in BCP compared with an equivalent change in PM(2.5) mass.
BCP is a valuable additional air quality indicator to evaluate the health risks of air quality dominated by primary combustion particles.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
The oxidative potential (OP) of particulate matter (PM) has been proposed as a more health relevant metric than PM mass. Different assays exist for measuring OP and little is known about how the ...different assays compare.
To assess the OP of PM collected at different site types and to evaluate differences between locations, size fractions and correlation with PM mass and PM composition for different measurement methods for OP.
PM2.5 and PM10 was sampled at 5 sites: an underground station, a farm, 2 traffic sites and an urban background site. Three a-cellular assays; dithiothreitol (OPDTT), electron spin resonance (OPESR) and ascorbate depletion (OPAA) were used to characterize the OP of PM.
The highest OP was observed at the underground, where OP of PM10 was 30 (OPDTT) to >600 (OPESR) times higher compared to the urban background when expressed as OP/m3 and 2–40 times when expressed as OP/μg. For the outdoor sites, samples from the farm showed significantly lower OPESR and OPAA, whereas samples from the continuous traffic site showed the highest OP for all assays. Contrasts in OP between sites were generally larger than for PM mass and were lower for OPDTT compared to OPESR and OPAA. Furthermore, OPDTT/μg was significantly higher in PM2.5 compared to PM10, whereas the reverse was the case for OPESR. OPESR and OPAA were highly correlated with traffic-related PM components (i.e. EC, Fe, Cu, PAHs), whereas OPDTT showed the highest correlation with PM mass and OC.
Contrasts in OP between sites, differences in size fractions and correlation with PM composition depended on the specific OP assay used, with OPESR and OPAA showing the most similar results. This suggests that either OPESR or OPAA and OPDTT can complement each other in providing information regarding the oxidative properties of PM, which can subsequently be used to study its health effects.
•The oxidative potential (OP) of PM was highly elevated at an underground station.•Outdoors, PM along a highway with continuous traffic showed the highest activity.•Contrasts in OP between sites depended on the specific OP assay used.•The OP methods studied also differed in respect to correlation with PM composition.•Different OP assays can provide complementary data about the oxidative properties of PM.
Evidence is emerging that poor mental health is associated with the environmental exposures of surrounding green, air pollution and traffic noise. Most studies have evaluated only associations of ...single exposures with poor mental health.
To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health.
In this cross-sectional study, we linked data from a Dutch national health survey among 387,195 adults including questions about psychological distress, based on the Kessler 10 scale, to an external database on registered prescriptions of anxiolytics, hypnotics & sedatives and antidepressants. We added data on residential surrounding green in a 300 m and a 1000 m buffer based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), modeled annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), and nitrogen dioxide (NO2)) and modeled road- and rail-traffic noise (Lden and Lnight) to the survey. We used logistic regression to analyze associations of surrounding green, air pollution and traffic noise exposure with poor mental health.
In single exposure models, surrounding green was inversely associated with poor mental health. Air pollution was positively associated with poor mental health. Road-traffic noise was only positively associated with prescription of anxiolytics, while rail-traffic noise was only positively associated with psychological distress. For prescription of anxiolytics, we found an odds ratio OR of 0.88 (95% CI: 0.85, 0.92) per interquartile range IQR increase in NDVI within 300 m, an OR of 1.14 (95% CI: 1.10, 1.19) per IQR increase in NO2 and an OR of 1.07 (95% CI: 1.03, 1.11) per IQR increase in road-traffic noise. In multi exposure analyses, associations with surrounding green and air pollution generally remained but attenuated. Joint odds ratios JOR, based on the Cumulative Risk Index (CRI) method, of combined exposure to air pollution, traffic noise and decreased surrounding green were higher than the ORs of single exposure models. Associations of environmental exposures with poor mental health differed somewhat by age.
Studies including only one of these three correlated exposures may overestimate the influence of poor mental health attributed to the studied exposure, while underestimating the influence of combined environmental exposures.
•Surrounding green was inversely associated with poor mental health.•Air pollution and to a limited extent traffic noise were positively associated with poor mental health.•In multi exposure models, associations with surrounding green and air pollution attenuated, but remained significant.•The most consistent associations were observed with prescription of anxiolytics and prescription of hypnotics & sedatives.•Joint odds ratios of combined exposure were higher than the ORs of single exposure models.
Ambient particulate matter (PM) exposure is associated with respiratory and cardiovascular morbidity and mortality. To what extent such effects are different for PM obtained from different sources or ...locations is still unclear. This study investigated the in vitro toxicity of ambient PM collected at different sites in the Netherlands in relation to PM composition and oxidative potential.
PM was sampled at eight sites: three traffic sites, an underground train station, as well as a harbor, farm, steelworks, and urban background location. Coarse (2.5-10 μm), fine (< 2.5 μm) and quasi ultrafine PM (qUF; < 0.18 μm) were sampled at each site. Murine macrophages (RAW 264.7 cells) were exposed to increasing concentrations of PM from these sites (6.25-12.5-25-50-100 μg/ml; corresponding to 3.68-58.8 μg/cm2). Following overnight incubation, MTT-reduction activity (a measure of metabolic activity) and the release of pro-inflammatory markers (Tumor Necrosis Factor-alpha, TNF-α; Interleukin-6, IL-6; Macrophage Inflammatory Protein-2, MIP-2) were measured. The oxidative potential and the endotoxin content of each PM sample were determined in a DTT- and LAL-assay respectively. Multiple linear regression was used to assess the relationship between the cellular responses and PM characteristics: concentration, site, size fraction, oxidative potential and endotoxin content.
Most PM samples induced a concentration-dependent decrease in MTT-reduction activity and an increase in pro-inflammatory markers with the exception of the urban background and stop & go traffic samples. Fine and qUF samples of traffic locations, characterized by a high concentration of elemental and organic carbon, induced the highest pro-inflammatory activity. The pro-inflammatory response to coarse samples was associated with the endotoxin level, which was found to increase dramatically during a three-day sample concentration procedure in the laboratory. The underground samples, characterized by a high content of transition metals, showed the largest decrease in MTT-reduction activity. PM size fraction was not related to MTT-reduction activity, whereas there was a statistically significant difference in pro-inflammatory activity between Fine and qUF PM. Furthermore, there was a statistically significant negative association between PM oxidative potential and MTT-reduction activity.
The response of RAW264.7 cells to ambient PM was markedly different using samples collected at various sites in the Netherlands that differed in their local PM emission sources. Our results are in support of other investigations showing that the chemical composition as well as oxidative potential are determinants of PM induced toxicity in vitro.
IntroductionThe oxidative potential (OP) of particulate matter (PM) has been proposed as a health-relevant metric, but currently few epidemiological studies investigated associations of OP with ...health. Our main aim was to assess associations of long-term exposure to OP with respiratory health in children. Our second aim was to evaluate whether OP is more consistently associated with respiratory health than PM mass, PM composition or nitrogen dioxide (NO2).MethodsFor 3701 participants of a prospective birth cohort, annual average concentrations of OP (assessed by spin resonance (OPESR) and dithiothreitol assay (OPDTT)), PM with an aerodynamic diameter of less than 2.5 µm (PM2.5) mass, NO2, and PM2.5 constituents at the home addresses at birth and at all follow-up addresses were estimated by land-use regression. Repeated questionnaire reports of asthma and hay fever until age 14 years, and measurements of allergic sensitisation, lung function and fractional exhaled nitric oxide at age 12 years were linked with air pollution concentrations.ResultsAsthma incidence, prevalence of asthma symptoms and rhinitis were positively associated with OPDTT (adjusted OR (95% CI) per IQR increase in exposure 1.10 (1.01 to 1.20), 1.08 (1.02 to 1.16), 1.15 (1.05 to 1.26), respectively). These associations persisted after adjustment for most co-pollutants. Forced expiratory volume in 1s and forced vital capacity were negatively associated with OPDTT. These associations were sensitive to adjustment for NO2. Respiratory health was not significantly associated with PM2.5 mass and OPESR.ConclusionsRespiratory health was more strongly associated with OPDTT than with PM2.5 mass; OPDTT associations with lung function, but not symptoms, were sensitive to adjustment for NO2.
Surrounding green, air pollution, and noise have been associated with cardiometabolic diseases, but most studies have assessed only one of these correlated exposures.
We aimed to evaluate ...associations of combined exposures to green, air pollution, and road traffic noise with cardiometabolic diseases.
In this cross-sectional study, we studied associations between self-reported physician-diagnosed diabetes, hypertension, heart attack, and stroke from a Dutch national health survey of 387,195 adults and residential surrounding green, annual average air pollutant concentrations including particulate matter with aerodynamic diameter Formula: see text (Formula: see text), PM with aerodynamic diameter Formula: see text (Formula: see text), nitrogen dioxide (Formula: see text), and oxidative potential (OP) with the dithiothreitol (DTT) assay (Formula: see text) and road traffic noise. Logistic regression models were used to analyze confounding and interaction of surrounding green, air pollution, and noise exposure.
In single-exposure models, surrounding green was inversely associated with diabetes, while air pollutants (Formula: see text, Formula: see text) and road traffic noise were positively associated with diabetes. In two-exposure analyses, associations with green and air pollution were attenuated but remained. The association between road traffic noise and diabetes was reduced to unity when adjusted for surrounding green or air pollution. Air pollution and surrounding green, but not road traffic noise, were associated with hypertension in single-exposure models. The weak inverse association of surrounding green with hypertension attenuated and lost significance when adjusted for air pollution. Only Formula: see text was associated with stroke and heart attack.
Studies including only one of the correlated exposures surrounding green, air pollution, and road traffic noise may overestimate the association of diabetes and hypertension attributed to the studied exposure. https://doi.org/10.1289/EHP3857.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Abstract
Due to the wealth of exposome data from longitudinal cohort studies that is currently available, the need for methods to adequately analyze these data is growing. We propose an approach in ...which machine learning is used to identify longitudinal exposome-related predictors of health, and illustrate its potential through an application. Our application involves studying the relation between exposome and self-perceived health based on the 30-year running Doetinchem Cohort Study. Random Forest (RF) was used to identify the strongest predictors due to its favorable prediction performance in prior research. The relation between predictors and outcome was visualized with partial dependence and accumulated local effects plots. To facilitate interpretation, exposures were summarized by expressing them as the average exposure and average trend over time. The RF model’s ability to discriminate poor from good self-perceived health was acceptable (Area-Under-the-Curve = 0.707). Nine exposures from different exposome-related domains were largely responsible for the model’s performance, while 87 exposures seemed to contribute little to the performance. Our approach demonstrates that ML can be interpreted more than widely believed, and can be applied to identify important longitudinal predictors of health over the life course in studies with repeated measures of exposure. The approach is context-independent and broadly applicable.
Everyday people are exposed to multiple environmental factors, such as surrounding green, air pollution and traffic noise. These exposures are generally spatially correlated. Hence, when estimating ...associations of surrounding green, air pollution or traffic noise with health outcomes, the other exposures should be taken into account. The aim of this study was to evaluate associations of long-term residential exposure to surrounding green, air pollution and traffic noise with mortality.
We followed approximately 10.5 million adults (aged ≥ 30 years) living in the Netherlands from 1 January 2013 until 31 December 2018. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 and 1000 m), annual average ambient air pollutant concentrations including particulate matter (PM
), nitrogen dioxide (NO
) and traffic noise with non-accidental and cause-specific mortality, adjusting for potential confounders.
In single-exposure models, surrounding green was negatively associated with all mortality outcomes, while air pollution was positively associated with all outcomes. In two-exposure models, associations of surrounding green and air pollution attenuated but remained. For respiratory mortality, in a two-exposure model with NO
and NDVI 300 m, the HR of NO
was 1.040 (95%CI: 1.022, 1.059) per IQR increase (8.3 µg/m
) and the HR of NDVI 300 m was 0.964 (95%CI: 0.952, 0.976) per IQR increase (0.14). Road-traffic noise was positively associated with lung cancer mortality only, also after adjustment for air pollution or surrounding green.
Lower surrounding green and higher air pollution were associated with a higher risk of non-accidental and cause-specific mortality. Studies including only one of these correlated exposures may overestimate the associations with mortality of that exposure.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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